Skip to main content
Glama
brightdata

Bright Data MCP

Official
by brightdata

search_engine

Read-only

Scrape Google, Bing, or Yandex search results and return SERP data as JSON or Markdown to gather current information, news, and detailed results.

Instructions

Scrape search results from Google, Bing or Yandex. Returns SERP results in JSON or Markdown (URL, title, description),Ideal forgathering current information, news, and detailed search results.

Input Schema

NameRequiredDescriptionDefault
queryYes
cursorNoPagination cursor for next page
engineNogoogle
geo_locationNo2-letter country code for geo-targeted results (e.g., "us", "uk")

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.9.3

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, openWorldHint and destructiveHint=false, so safety is covered. The description adds the return content, but its claim of "JSON or Markdown" output is unactionable since no format parameter exists in the schema, and pagination via the cursor is never explained. Net: some added value with a mild misleading note.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with the core capability front-loaded and no padding. A typo ("description),Ideal forgathering") slightly hurts polish but not comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-parameter, no-output-schema search tool, the description covers the source engines, the return payload fields, and the intended use case. The remaining gaps (pagination, format selection) are minor and largely resolvable from the schema's cursor field.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50% – only cursor and geo_location are documented in the schema. The description adds meaning to the engine enum by naming Google, Bing and Yandex, but says nothing about the required query or geo-targeting, so the undocumented half is only partially compensated.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Scrape search results from Google, Bing or Yandex") and names the output shape (SERP results with URL, title, description). It does not, however, differentiate itself from the sibling search_engine_batch, leaving the agent to infer when the single-query variant is preferred.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Ideal for gathering current information, news, and detailed search results" gives a use-case context, but there are no when-not conditions and no named alternative despite a sibling search_engine_batch existing. Usage is implied rather than prescribed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.